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Comparison of Different Image Enhancement Methods for Effective Whole-Body Bone Scan Image

Received: 14 June 2019     Accepted: 23 July 2019     Published: 28 August 2019
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Abstract

Nuclear medicine is one of the most important diagnostic tools used for different types of investigations such as a thyroid scan, renal function and whole-body bone scan. The main problem in nuclear medicine imaging system is the resulting images degraded with large amounts of noise. In this work we want use four different enhancement methods to enhance whole-body bone scan image so as to reduce the noise from the image and improve the resolution to achieve a better image quality and maintain quality for accurate diagnosis. Histogram equalization, adaptive histogram equalization, log transformation and gamma correction algorithms were used to improve the image quality. Four pair of bone scan images from gamma camera were used to perform this work. Enhanced images were quantified and evaluated by calculating the Peak Signal Noise Ratio, Mean Square Error and entropy. The result shows that the gamma correction algorithm gives best result among the four algorithms used for enhancing the bone images. The gamma correction algorithm can assist the radiologist in diagnosis the patient and quantify any changes accurately and quickly.

Published in Advances in Bioscience and Bioengineering (Volume 7, Issue 3)
DOI 10.11648/j.abb.20190703.16
Page(s) 55-59
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Whole-body Bone Scan, Gamma Camera, Image Enhancement, Nuclear Medicine

References
[1] S. Cherry, J. Sorenson, M. Phelps, physics in Nuclear Medicine, 3rd Edition, Elsevier 2000.
[2] J. Mallard, M. Myers, clinical application of gamma camera, physics in medicine and biology, vol. 8 (2).
[3] A. Kantzas, et al., Application of gamma camera imaging and SPECT systems in chemical processes chemical engineering journal, vol. 77 (1-2), 2000, pp: 19-25.
[4] R. Gonzalez, R. Woods, Digital Image Processing, second Edition, Prentice Hall, Inc, 2002.
[5] R. Gonzalez, R. Woods, Steven L. Eddins, Digital Image Processing using MATLAB, 2end Edition, Gatesmark Publishing, 2009.
[6] D. Chang, W. Wu, Image contrast enhancement based on a histogram transformation of local standard deviation, IEEE transaction on medical imaging, vol. 17 (4), 1998, pp. 518-531.
[7] R. Senthilkumar, M. Senthilmurugan, TRIAD histogram to enhance chest X-ray image, international journal of advanced research in computer and communication engineering, vol. 3 (11), 2014, pp. 8577-8580.
[8] J. A. Stark, W. J. Fitzgerald, An Alternative Algorithm for Adaptive Histogram Equalization, Graphical Models and Image Processing, vol. 58 (2), 1996.
[9] Urvashi Manikpuri, Yojana Yadav, Image Enhancement through Logarithmic Transformation, international journal of innovation research in advanced engineering, 2014, 357-362.
[10] S. Suman, et al. Image enhancement using geometric mean filter and gamma correction for WCE images, ICONIP, 2014, pp. 276-283.
[11] K. Somasundaram, P. Kalavath Medical Image Contrast Enhancement based on Gamma Correction 2014.
[12] M. Ouvrier, S. Vignot, J. Thariat. [State of the art in nuclear imaging for the diagnosis of bone metastases]. Bull Cancer. 2013 Nov. 100 (11): 1115-1124. [Medline].
[13] D. Sonker, Comparison of Histogram Equalization Techniques for Image Enhancement of Grayscale images in Natural and Unnatural Light, international journal of engineering research and development, Vol. 8 (9), 2013, pp. 57-61.
[14] S. Zobly et al, Selecting Suitable Gamma Value for Bone Scan Image Enhancement using Gamma Correction Method, Red Sea University Journal of Basic & Applied science, vol. 2 (1), 2017, pp. 485-490.
[15] A. Aslantas et al, A computer-aided Diagnosis System for Whole Body Bone Scintigraphy Scans, J Can Res Ther 2016, pp. 87-92.
[16] Zobly S. and Elfadel M., Whole-Body Bone Scan Image Enhancement Algorithms, 2018 International Conference on Computer, Control, Electrical and Electronic Engineering (ICCCEEE), Khartoum, 2018, pp. 1-4.
[17] X. Liu, An Improved Image Enhancement Algorithm Based on Fuzzy Set, 2012 International Conference on Medical Physics and Biomedical Engineering, 2012, 790-797.
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  • APA Style

    Sulieman Mohammed Salih Zobly. (2019). Comparison of Different Image Enhancement Methods for Effective Whole-Body Bone Scan Image. Advances in Bioscience and Bioengineering, 7(3), 55-59. https://doi.org/10.11648/j.abb.20190703.16

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    ACS Style

    Sulieman Mohammed Salih Zobly. Comparison of Different Image Enhancement Methods for Effective Whole-Body Bone Scan Image. Adv. BioSci. Bioeng. 2019, 7(3), 55-59. doi: 10.11648/j.abb.20190703.16

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    AMA Style

    Sulieman Mohammed Salih Zobly. Comparison of Different Image Enhancement Methods for Effective Whole-Body Bone Scan Image. Adv BioSci Bioeng. 2019;7(3):55-59. doi: 10.11648/j.abb.20190703.16

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  • @article{10.11648/j.abb.20190703.16,
      author = {Sulieman Mohammed Salih Zobly},
      title = {Comparison of Different Image Enhancement Methods for Effective Whole-Body Bone Scan Image},
      journal = {Advances in Bioscience and Bioengineering},
      volume = {7},
      number = {3},
      pages = {55-59},
      doi = {10.11648/j.abb.20190703.16},
      url = {https://doi.org/10.11648/j.abb.20190703.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.abb.20190703.16},
      abstract = {Nuclear medicine is one of the most important diagnostic tools used for different types of investigations such as a thyroid scan, renal function and whole-body bone scan. The main problem in nuclear medicine imaging system is the resulting images degraded with large amounts of noise. In this work we want use four different enhancement methods to enhance whole-body bone scan image so as to reduce the noise from the image and improve the resolution to achieve a better image quality and maintain quality for accurate diagnosis. Histogram equalization, adaptive histogram equalization, log transformation and gamma correction algorithms were used to improve the image quality. Four pair of bone scan images from gamma camera were used to perform this work. Enhanced images were quantified and evaluated by calculating the Peak Signal Noise Ratio, Mean Square Error and entropy. The result shows that the gamma correction algorithm gives best result among the four algorithms used for enhancing the bone images. The gamma correction algorithm can assist the radiologist in diagnosis the patient and quantify any changes accurately and quickly.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Comparison of Different Image Enhancement Methods for Effective Whole-Body Bone Scan Image
    AU  - Sulieman Mohammed Salih Zobly
    Y1  - 2019/08/28
    PY  - 2019
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    T2  - Advances in Bioscience and Bioengineering
    JF  - Advances in Bioscience and Bioengineering
    JO  - Advances in Bioscience and Bioengineering
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    PB  - Science Publishing Group
    SN  - 2330-4162
    UR  - https://doi.org/10.11648/j.abb.20190703.16
    AB  - Nuclear medicine is one of the most important diagnostic tools used for different types of investigations such as a thyroid scan, renal function and whole-body bone scan. The main problem in nuclear medicine imaging system is the resulting images degraded with large amounts of noise. In this work we want use four different enhancement methods to enhance whole-body bone scan image so as to reduce the noise from the image and improve the resolution to achieve a better image quality and maintain quality for accurate diagnosis. Histogram equalization, adaptive histogram equalization, log transformation and gamma correction algorithms were used to improve the image quality. Four pair of bone scan images from gamma camera were used to perform this work. Enhanced images were quantified and evaluated by calculating the Peak Signal Noise Ratio, Mean Square Error and entropy. The result shows that the gamma correction algorithm gives best result among the four algorithms used for enhancing the bone images. The gamma correction algorithm can assist the radiologist in diagnosis the patient and quantify any changes accurately and quickly.
    VL  - 7
    IS  - 3
    ER  - 

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Author Information
  • Department of Physics & Medical Instrumentation, University of Gezira, Medani, Sudan

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